Method run

Core/Variational/Optimizer.cpp:89–112

}

bool VanillaGradientDescentOptimizer::run(
        std::vector<var> &leaves,
        size_t t)
{    
    (void)(t);

    std::unordered_map<var, MatrixXd> gradient;
    for (auto iter : leaves)
    {
        gradient[iter] = zeros_like(iter);
    }

    auto leaf_set = m_cost_function.findNonConsts(leaves);
    auto var = m_cost_function.getRoot();

    eval(var, true);
    back(m_cost_function, gradient, leaf_set);
    for (auto iter : leaves)
    {
        iter.setValue(iter.getValue() - m_learning_rate * gradient[iter]);
    }

    return true;
}

MomentumOptimizer::MomentumOptimizer(
        var lost,